17 citations · 38 across the 13 of their papers we have counts for
14 papers
Self-Supervised Skill Optimization
Siran Peng, Cuiyu Yang, Tianyu Fu +9
Agent skills provide frozen large language model (LLM) agents with reusable procedural guidance, and recent work shows that such skills can be optimized with ground-truth (GT) feed…
Private Face Recognition Training Dataset Publication via Identity-Decoupled and Geometry-Preserving Face Distillation
Shuhuan Chen, Xiangyu Zhu, Weisong Zhao +6
Publishing private face recognition~(FR) training datasets is privacy-sensitive because faces expose identity information. Private FR training dataset publication mitigates this ri…
Knowing You at First Glance: Inferring Apparent Personality from Faces
Shuhuan Chen, Xiangyu Zhu, Weisong Zhao +3
Inferring apparent personality from facial images is important in social scenarios for embodied agents in human-robot interaction. Unlike inferring intrinsic personality traits via…
Direct Discrepancy Replay: Distribution-Discrepancy Condensation and Manifold-Consistent Replay for Continual Face Forgery Detection
Tianshuo Zhang, Haoyuan Zhang, Siran Peng +3
Continual face forgery detection (CFFD) requires detectors to learn emerging forgery paradigms without forgetting previously seen manipulations. Existing CFFD methods commonly rely…
One Ring to Rule Them All: Unifying Group-Based RL via Dynamic Power-Mean Geometry
Weisong Zhao, Tong Wang, Zichang Tan +11
Group-based reinforcement learning has evolved from the arithmetic mean of GRPO to the geometric mean of GMPO. While GMPO improves stability by constraining a conservative objectiv…
UPA: Unsupervised Prompt Agent via Tree-Based Search and Selection
Siran Peng, Weisong Zhao, Tianyu Fu +6
Prompt agents have recently emerged as a promising paradigm for automated prompt optimization, framing prompt discovery as a sequential decision-making problem over a structured pr…
DiffusionFF: A Diffusion-based Framework for Joint Face Forgery Detection and Fine-Grained Artifact Localization
Siran Peng, Haoyuan Zhang, Li Gao +5
The rapid evolution of deepfake technologies demands robust and reliable face forgery detection algorithms. While determining whether an image has been manipulated remains essentia…
RealisVSR: Detail-enhanced Diffusion for Real-World 4K Video Super-Resolution
Weisong Zhao, Jingkai Zhou, Xiangyu Zhu +4
Video Super-Resolution (VSR) has achieved significant progress through diffusion models, effectively addressing the over-smoothing issues inherent in GAN-based methods. Despite rec…
Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +56
Synthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including…
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy
Te Yang, Jian Jia, Xiangyu Zhu +9
Large Language Models (LLMs) have strong instruction-following capability to interpret and execute tasks as directed by human commands. Multimodal Large Language Models (MLLMs) hav…
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +55
Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class v…
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…
Cross Architecture Distillation for Face Recognition
Weisong Zhao, Xiangyu Zhu, Zhixiang He +2
Transformers have emerged as the superior choice for face recognition tasks, but their insufficient platform acceleration hinders their application on mobile devices. In contrast,…
Grouped Knowledge Distillation for Deep Face Recognition
Weisong Zhao, Xiangyu Zhu, Kaiwen Guo +2
Compared with the feature-based distillation methods, logits distillation can liberalize the requirements of consistent feature dimension between teacher and student networks, whil…